Distributed acoustic machine learning models are not exceptions.
Among the various problem domains in distributed computing, acoustic machine learning is useful in various applications, including classification of different kinds of sounds in city streets [1]}, detecting anomalies in industrial settings [2]}, [3]}, identifying health problems by observing body sounds [4]}, and tracing species in danger by tracking their sounds [5]}.
